994 resultados para Wind forecast


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It has been well documented that the consensus forecast from surveys of professional forecasters shows a bias that varies over time. In this paper, we examine whether this bias may be due to forecasters having an asymmetric loss function. In contrast to previous research, we account for the time variation in the bias by making the loss function depend on the state of the economy. The asymmetry parameter in the loss function is specified to depend on set state variables which may cause forecaster to intentionally bias their forecasts. We consider both the Lin–Ex and asymmetric power loss functions. For the commonly used Lin–Ex and Lin–Lin loss functions, we show the model can be easily estimated by least squares. We apply our methodology to the consensus forecast of real U.S. GDP growth from the Survey of Professional Forecasters. We find that forecast uncertainty has an asymmetric effect on the asymmetry parameter in the loss function dependent upon whether the economy is in expansion or contraction. When the economy is in expansion, forecaster uncertainty is related to an overprediction in the median forecast of real GDP growth. In contrast, when the economy is in contraction, forecaster uncertainty is related to an underprediction in the median forecast of real GDP growth. Our results are robust to the particular loss function that is employed in the analysis.

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We collaborate with environmental scientists to study the hydrodynamics and water quality in an urban district, where the surface wind distribution is an essential input but undergoes high spatial and temporal variations due to the complex urban landform created by surrounding buildings. In this work, we study an optimal sensor placement scheme to measure the wind distribution over a large urban reservoir with a limited number of wind sensors. Unlike existing sensor placement solutions that assume Gaussian process of target phenomena, this study measures the wind which inherently exhibits strong non-Gaussian yearly distribution. By leveraging the local monsoon characteristics of wind, we segment a year into different monsoon seasons which follow a unique distribution respectively. We also use computational fluid dynamics to learn the spatial correlation of wind in the presence of surrounding buildings. The output of sensor placement is a set of the most informative locations to deploy the wind sensors, based on the readings of which we can accurately predict the wind over the entire reservoir surface in real time. 10 wind sensors are finally deployed around or on the water surface of an urban reservoir. The in-field measurement results of more than 3 months suggest that the proposed sensor placement and spatial prediction approach provides accurate wind measurement which outperforms the state-of-the-art Gaussian model based or interpolation based approaches.

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This paper proposes an effective VAR planning based on reactive power margin for the enhancement of dynamic voltage stability in distribution networks with distributed wind generation. The analysis is carried over a distribution test system representative of the Kumamoto area in Japan. The detailed mathematical modeling of the system is also presented. Firstly, this paper provides simulation results showing the effects of composite load on voltage dynamics in the distribution network through an accurate time-domain analysis. Then, a cost-effective combination of shunt capacitor bank and distribution static synchronous compensator (D-STATCOM) is selected to ensure fast voltage recovery after a sudden disturbance. The analysis shows that the proposed approach can reduce the size of compensating devices, which in turn, reduces the cost. It also reduces power loss of the system.

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This paper proposes a distributed generator (DG) placement methodology based on newly defined term reactive power loadability. The effectiveness of the proposed planning is carried out over a distribution test system representative of the Kumamoto area in Japan. Firstly, this paper provides simulation results showing the sensitivity of the location of renewable energy based DG on voltage profile and stability of the system. Then, a suitable location is identified for two principal types DG, i. e., wind and solar, separately to enhance the stability margin of the system. The analysis shows that the proposed approach can reduce the power loss of the system, which in turn, reduces the size of compensating devices.

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This paper presents potential barriers to integrate the squirrel cage induction generator (SCIG) and doubly fed induction generator (DFIG) type wind turbine in distribution networks. The analysis is carried out over a 16 bus distribution test system. Both static and dynamic analyses are performed to see the impact of two different generators on the distribution system. The simulation results show that both SCIG and DFIG type wind turbines have significant impact on the static voltage stability, power loss, and dynamic behavior of the system, which should be taken into account to improve systems performance before integrating wind generation in existing distribution networks.

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This paper presents the application of FACTS devices for the enhancement of dynamic voltage stability in distribution networks with distributed wind generation. The analysis is carried over a test distribution system representative of the Kumamoto area in Japan. The detailed mathematical modelling of the system is also presented. Firstly, this paper provides simulation results showing the effects of higher and lower penetration of distributed wind generation on the voltage dynamics in a faulted system. Then, a distribution static synchronous compensator (D-STATCOM) is used to improve the voltage profile of the system. This analysis shows that D-STATCOM has significant performance to improve the voltage dynamics of distribution system compared to shunt capacitor.

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This paper presents the impact of different types of load models in distribution network with distributed wind generation. The analysis is carried out for a test distribution system representative of the Kumamoto area in Japan. Firstly, this paper provides static analysis showing the impact of static load on distribution system. Then, it investigates the effects of static as well as composite load based on the load composition of IEEE task force report [1] through an accurate time-domain analysis. The analysis shows that modeling of loads has a significant impact on the voltage dynamics of the distribution system with distributed generation.

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In this paper, simulation results showing the effect of lower and higher penetration of distributed wind generation on the voltage profile in distribution systems have been presented. The analysis is carried out over two distribution test systems. The detailed mathematical modeling of the system is also presented. It also investigates the small-signal stability of distribution systems using eigenvalue approach. The analyses show that voltage variation problems occur in different nodes of the distribution networks with an increase of penetration level. However, proper selection of dispersion level can improve the voltage profile of the distribution systems

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This paper proposes a decentralised controller design for doubly-fed induction generators (DFIGs) to enhance dynamic performance of distribution networks. The change in the output power due to the variable nature of wind is considered as an uncertain term in the design algorithm. In addition, the interconnection effect of the other subsystems are considered in the design process. The H norm of the uncertain system is found out and simultaneous output-feedback linear controllers are designed based controller is verified on a 16 bus distribution test system for severe disturbances. Simulation results indicate that the designed controller is robust against uncertainties in operating conditions

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The phenomenal growth in economy experienced in developed countries throughout the 20th century has largely been driven by the availability of conventional energy sources for electricity generation. However, increased concern about fossil fuels and adverse effect of carbon dioxide emission in to atmosphere changed the conventional power system to a viable one by integrating renewable energy sources into the existing system. Among the Renewable Energy (RE) sources, wind energy is one of the fastest growing technologies in reducing the Green House Gas (GHG) emissions in to the atmosphere due to its continuous availability throughout a period. Hence, this paper discusses the performance of a wind-grid connected system in a semi-arid region by conducting a case study. Wilson promontory, one of the best locations for wind generation in Victoria is considered as a case study. Hybrid Optimization Model for Electric Renewable (HOMER) is used as a simulating tool for this analysis. This study also presents the influences of storage system in the proposed Hybrid Power System (HPS) allowing energy to be stored during higher generations or lower load demands. In addition this paper also discusses the major integration issues to facilitate the large scale wind energy into the grid for reliable power generation and distribution.

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This paper proposes a hybrid computational framework based on Sequential Quadratic Programming (SQP) and Particle Swarm Optimization (PSO) to address the Combined Unit Commitment and Emission (CUCE) problem. By considering a model which includes both thermal generators and wind farms, the proposed hybrid computational framework can minimize the scheduling cost and greenhouse gases emission cost. The viability of the proposed hybrid technique is demonstrated using a set of numerical case studies. Moreover, comparisons are performed with other optimization algorithms. The simulation results show that our hybrid method is better in terms of the speed and accuracy. The main contribution of this paper is the development of a emission unit commitment model integrating with wind energy and combining the SQP and PSO methods to achieve faster and better performance optimization

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 Urban Heat Island (UHI) has become a growing concern to the quality of densely built urban environments, particularly in tropical cities. Wind speed has widely been reported to have decreased the intensity of heat island effect in urban areas. The cooling effect of the wind helps to mitigate the adverse effects of heat island on the micro climate and human thermal comfort. This paper investigates the existence of heat island in Muar, one of the fast growing cities in southern part of Malaysia and its possible causes, and then examines the effects of different urban geometry on the wind flow. The results of this study indicate that the chaotic development in Muar has caused reduced ventilation in urban canyons. The heat island intensity in the city center was recorded as 4. °C during the day and 3.2. °C during the night. Investigation of various urban geometry modifications showed that step up configuration was the most effective geometry as it can distribute the wind evenly allowing the wind to reach even the leeward side of each building. © 2014 Elsevier Ltd.